Inattentive professional forecasters

TLDR: This paper used the ECB Survey of Professional Forecasters to characterize expectations at the micro-level, and found that forecasters fail to systematically update their forecasts and disagree even when updating, which is qualitatively supportive of recent models of inattention.

About: This article is published in Journal of Monetary Economics.The article was published on 2013-11-01 and is currently open access. It has received 274 citations till now. The article focuses on the topics: Survey of Professional Forecasters & Sticky information.

Figures

Figure 7: Evolution of inattention

Table 3: Errors, disagreement & inattention

Figure 8: Evolution of inattention

Figure 5: Distribution of inflation forecasts over time

Table 7: Minimum Distance Estimation and Tests

Figure 11: Implied disagreement: 1-year, HICP

Frequently asked questions

Q1. What have the authors contributed in "Inattentive professional forecasters∗" ?

The authors provide a micro data estimation of the extent of inattention among professional forecasters. The authors show that, on their sample, about 20 % of professional forecasters are inattentive to new information released each quarter. 

Q2. What future works have the authors mentioned in the paper "Inattentive professional forecasters∗" ?

At least two avenues for future research are worthwhile considering. First, the methodology implemented in this paper may be used to investigate other panel data sets of expectations such as consumer and firms expectations. Second, results in the present paper suggest that the sticky information model should be altered in order to replicate the main features of the data namely the coexistence of disagreement and a significant degree of attention, together with smooth forecasts. 

Q3. Why do the authors focus on the quantitative assessment of the sticky information model?

Because imperfect information models cannot rationalize why the frequency of forecast updating is lower from one, the authors focus on a quantitative assessmentof the sticky information model à la Mankiw-Reis. 

Q4. What is the effect of attention on forecast errors?

in a sticky information approach, more attention therefore more forecast updates, should also lead to less differences among forecasters, the fraction of forecasters relying on the most updated information increasing. 

Q5. What is the originality of the approach?

The originality of their approach is to rely on one specificity of the European SPF, which is to provide sequences of individual forecasts for the same event (variable and date). 

Q6. What is the probability of a forecaster revising at a given time?

One may wonder if professional forecasters decide to allocate limited computational capacities, by shifting attention toward the most fluctuating variable at the time they forecast. 

Q7. What is the reason why the sticky information model is not supported by the data?

The sticky information model is not supported by the data in that the inattention is not able to generate both disagreement and forecast errors that are in line with the observations. 

Q8. What is the evidence in favor of systematic bias?

As Pesaran and Wheale (2006) recall, when large sample sizes are considered, the evidence in favor of systematic bias tends to disappear.